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Institutional Segmentation, Inequality in Work Opportunities, and Income in Digital Labor Markets: Evidence Based on Witkey Transactions

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  • Shengqiang Zuo
  • Jun Feng

Abstract

Digital technologies are rapidly transforming the world of work, creating digital labor markets. Based on transaction cost theory and labor market segmentation theory, this study adopts binary logistic and multiple regression models and uses EPWK transaction data (n = 21,808) to empirically examine the institutional segmentation phenomenon of digital labor markets. This study finds institutional segmentation existing in such markets, owing to differences in the Witkey level among employees, thus leading to inequality in work opportunities and labor remuneration income. Further, transaction mode and task type moderate the segmentation phenomenon. Suggestions are offered to reduce institutional segmentation by improving the platform system.

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  • Shengqiang Zuo & Jun Feng, 2023. "Institutional Segmentation, Inequality in Work Opportunities, and Income in Digital Labor Markets: Evidence Based on Witkey Transactions," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 59(15), pages 4125-4137, December.
    • Handle: RePEc:mes:emfitr:v:59:y:2023:i:15:p:4125-4137
    DOI: 10.1080/1540496X.2023.2179874
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